Description Usage Arguments Author(s) See Also Examples
View source: R/get.landscape.FPK.MCMC.R
The function plots the median value of the macroevolutionary landscape across the posterior in a solid line and draws a polygon that streches between two quantiles of the posterior.
1 2 3 4 
chain 
An data.frame object representing the output of an MCMC chain, as obtained by MH_MCMC_FPK. 
bounds 
The bounds on the trait interval 
Npts 
The number of points used in the discretization procedure. 
burnin 
The percentage of generations discarded as burnin. 
probs.CI 
A vector of the two quantiles of the posterior distribution between which samples should be considered. 
COLOR_MEDIAN 
The color used to plot the median macroevolutionary landscape across the posterior. 
COLOR_FILL 
The color used to plot the polygon that stretches between the two quantiles of the posterior. 
transparency 
The transparency used for plotting the polygon 
main 
Title of the graph. 
ylab 
y label of the graph. 
xlab 
X label of the graph. 
xlim 

ylim 
F.C. Boucher
MH_MCMC_FPK
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23  ## Not run:
# Simulate data: tree + continuous trait
library(geiger)
tree=sim.bdtree(stop='taxa',n=10) # tree with few tips for quick tests
tree$edge.length=100*tree$edge.length/max(branching.times(tree)) # rescale the tree
# Simulate trait evolving on a macroevolutionary landscape with two peaks of equal heights
x=seq(from=1.5,to=1.5,length.out=100)
bounds=c(min(x),max(x)) # the bounds we use for simulating: for technical purposes only
V6=10*(x^40.5*(x^2)+0.*x) # this is the evolutionary potential: it has two wells
TRAIT= Sim_FPK(tree,x0=0,V=V6,sigma=10,bounds=c(5, 5))
# Run a MCMC chain to fit the FPK model
MCMC=MH_MCMC_FPK(tree,trait=TRAIT,bounds=c(5,5),Nsteps=10000,record_every=100,
plot_every=100,Npts=20,pars_init=c(0,4,4,0,1),prob_update=c(0.2,0.25,0.25,0.25,0.05),
verbose=TRUE,plot=TRUE,save_to='MCMC_FPK_test.Rdata',save_every=100,
type_priors=c(rep('Normal',4),'Uniform'),
shape_priors=list(c(0,10),c(0,10),c(0,10),c(0,10),NA),proposal_type='Uniform',
proposal_sensitivity=c(0.1,0.1,0.1,0.1,1),prior.only=F)
get.landscape.FPK.MCMC(chain=MCMC,bounds=c(5,5),Npts=100,burnin=0.1,
probs.CI=c(0.025,0.975),COLOR_MEDIAN='red',COLOR_FILL='red',transparency=0.3,
main='Macroevolutionary landscapes MCMC',ylab='N.exp(V)',xlab='Trait',
xlim=NULL,ylim=NULL)
## End(Not run)

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